This document summarizes an approach called "non-combinatorial chemistry" for drug discovery. It involves designing and synthesizing individual compounds from large virtual libraries, rather than generating all combinations as in traditional combinatorial chemistry. This allows greater control over each compound's properties while exploiting large virtual libraries. The approach uses rational design, careful synthesis and purification of compounds before testing to generate high-quality biological data and identify novel drug leads.
Drug excipient incompatibilities are major concerns in formulation development.
Selection of the proper excipient during preformulation studies is of prime importance.
Drug excipient incompatibilities are major concerns in formulation development.
Selection of the proper excipient during preformulation studies is of prime importance.
Design, Synthesis, and Characterization of New 1,3,5-Trisubstituted-2-pyrazol...BRNSS Publication Hub
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Objective: The objective of the paper was to design, synthesis, and characterization of new 1,3,5-trisubstituted-2-pyrazolines derivative and to evaluate for analgesic potential. Materials and Methods: The 1,3,5-tri-substituted-2-pyrazolines derivatives have been synthesized by the reaction of chalcone derivatives with 4-hydrazinylbenzene sulfonamide hydrochloride and phenyl hydrazine hydrochloride. Total 16 compounds have been synthesized and characterized by the IR, 1HNMR, and mass spectral analysis. Proposed compounds have been evaluated for analgesic activity. The synthesized compounds also evaluated for the analgesic activity by the following two methods, that is, hot plate test method and acetic acid induced writhing in mice. Pentazocine and acetyl acetic acid were used as standard drug for compare the efficacy. Results and Discussion: The analgesic activity of the 16 synthesized compound series A1-A8, and B1-B8 has been evaluated using hot plate test method and acetic acid induced writhing in mice. The results of the evaluation have been viewed by taking pentazocine and acetyl acetic acid as the standard drug. In hot plate test, series A1-A8, shown delay the paw withdrawal latency time for compound A2 (10.30 s), A4 (9.45 s), A7 (11.65 s), and A8 (11.26 s) after 90 min. In series, B1-B8 shown delay the paw withdrawal latency time for compound B2 (9.10 s) and B7 (10.42 s) after 90 min, inhibit the pain sensation, and inhibit pain produced by thermal means. Synthesized compounds of series A1-A8, compounds A2, A5, A6, A7, and A8 were shown 83.00, 76.01, 80.34, 86.99, and 88.15 were shown percent inhibition, significantly (p<0.05 and p<0.001, respectively) and reduced the number of wriths induced by 0.6% acetic acid at the dose of 10 mg/kg. Acetylsalicylic acid (10 mg/kg) appears to be better effective in reducing the number of wriths, it significantly (P < 0.001) reduced the number of wriths by 99.0%. The compounds B1, B3, and B4 have shown least active activity. These all finding suggest that these synthesized compounds have the potential as analgesic agent. Conclusion: The 1,3,5-pyrazoline derivatives has been successfully synthesized and evaluated for analgesic activity of mice model and results data indicate that compounds A2, A5, A6, A7, and A8 were shown 83.00, 76.01, 80.34, 86.99, and 88.15%, and compounds B2, B7, and B8 were shown 72.25, 74.27, and 74.56% inhibitions. The presence of SO2NH2 is essential for analgesic activity.
2 Aspects of compatibility tests are:
Identification of compatible excipients for a formulation.
Identification of stable storage conditions
2 Types:
Solid state reactions: much slower and difficult to interpret.
Liquid state reactions: easier to detect
According to Stability Guidelines by FDA following conditions should be evaluated for solutions or suspensions
1. Acidic or alkaline pH.
2. Presence of added substances
3. High oxygen and nitrogen atmospheres.
4. Effect of stress testing conditions.
Design, Synthesis, Biological Evaluation, and In Silico ADMET Studies of 1,8-...BRNSS Publication Hub
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In the present study, 1,8-naphthyridine-3-carboxylic acid derivatives (5a1, 5a2, 5b1, and 5b2) were
designed, synthesized, and screened for their in vitro H1-antihistaminic activity. H1R inhibitory activity
of the synthesized derivatives was calculated by the modified Van Arman technique, histamine-induced
bronchoconstriction in guinea pigs. A good bronchorelaxant effect of compounds was observed in
histamine-contracted guinea pig tracheal chain through H1-receptor antagonism. In addition, the
hypothetically resulted compounds are checked for their reliability on other in silico drug designing
online web services like SwissADME predictor. In silico ADMET analysis results show that all the
derivatives had negligible toxicity, good absorption, and solubility profile. These compounds may serve
as possible lead for establishing safe and effective antihistaminic agent(s).
Design, Synthesis, and Characterization of New 1,3,5-Trisubstituted-2-pyrazol...BRNSS Publication Hub
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Objective: The objective of the paper was to design, synthesis, and characterization of new 1,3,5-trisubstituted-2-pyrazolines derivative and to evaluate for analgesic potential. Materials and Methods: The 1,3,5-tri-substituted-2-pyrazolines derivatives have been synthesized by the reaction of chalcone derivatives with 4-hydrazinylbenzene sulfonamide hydrochloride and phenyl hydrazine hydrochloride. Total 16 compounds have been synthesized and characterized by the IR, 1HNMR, and mass spectral analysis. Proposed compounds have been evaluated for analgesic activity. The synthesized compounds also evaluated for the analgesic activity by the following two methods, that is, hot plate test method and acetic acid induced writhing in mice. Pentazocine and acetyl acetic acid were used as standard drug for compare the efficacy. Results and Discussion: The analgesic activity of the 16 synthesized compound series A1-A8, and B1-B8 has been evaluated using hot plate test method and acetic acid induced writhing in mice. The results of the evaluation have been viewed by taking pentazocine and acetyl acetic acid as the standard drug. In hot plate test, series A1-A8, shown delay the paw withdrawal latency time for compound A2 (10.30 s), A4 (9.45 s), A7 (11.65 s), and A8 (11.26 s) after 90 min. In series, B1-B8 shown delay the paw withdrawal latency time for compound B2 (9.10 s) and B7 (10.42 s) after 90 min, inhibit the pain sensation, and inhibit pain produced by thermal means. Synthesized compounds of series A1-A8, compounds A2, A5, A6, A7, and A8 were shown 83.00, 76.01, 80.34, 86.99, and 88.15 were shown percent inhibition, significantly (p<0.05 and p<0.001, respectively) and reduced the number of wriths induced by 0.6% acetic acid at the dose of 10 mg/kg. Acetylsalicylic acid (10 mg/kg) appears to be better effective in reducing the number of wriths, it significantly (P < 0.001) reduced the number of wriths by 99.0%. The compounds B1, B3, and B4 have shown least active activity. These all finding suggest that these synthesized compounds have the potential as analgesic agent. Conclusion: The 1,3,5-pyrazoline derivatives has been successfully synthesized and evaluated for analgesic activity of mice model and results data indicate that compounds A2, A5, A6, A7, and A8 were shown 83.00, 76.01, 80.34, 86.99, and 88.15%, and compounds B2, B7, and B8 were shown 72.25, 74.27, and 74.56% inhibitions. The presence of SO2NH2 is essential for analgesic activity.
2 Aspects of compatibility tests are:
Identification of compatible excipients for a formulation.
Identification of stable storage conditions
2 Types:
Solid state reactions: much slower and difficult to interpret.
Liquid state reactions: easier to detect
According to Stability Guidelines by FDA following conditions should be evaluated for solutions or suspensions
1. Acidic or alkaline pH.
2. Presence of added substances
3. High oxygen and nitrogen atmospheres.
4. Effect of stress testing conditions.
Design, Synthesis, Biological Evaluation, and In Silico ADMET Studies of 1,8-...BRNSS Publication Hub
Â
In the present study, 1,8-naphthyridine-3-carboxylic acid derivatives (5a1, 5a2, 5b1, and 5b2) were
designed, synthesized, and screened for their in vitro H1-antihistaminic activity. H1R inhibitory activity
of the synthesized derivatives was calculated by the modified Van Arman technique, histamine-induced
bronchoconstriction in guinea pigs. A good bronchorelaxant effect of compounds was observed in
histamine-contracted guinea pig tracheal chain through H1-receptor antagonism. In addition, the
hypothetically resulted compounds are checked for their reliability on other in silico drug designing
online web services like SwissADME predictor. In silico ADMET analysis results show that all the
derivatives had negligible toxicity, good absorption, and solubility profile. These compounds may serve
as possible lead for establishing safe and effective antihistaminic agent(s).
Specialized in custom synthesis of organic molecules. Broad experience of working on multiple business models - FTEs, FFS, Milestone services of pharmaceutical industry.
Commited to deliver highest quality products in a timely manner and value to the customers.
Process chemistry AS PER PCI SYLLABUS FOR M.PHARMShikha Popali
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pharmaceutical process chemistry is process WHERE FROM THE RESEARCH TO FINISH PRODUCT INCLUDING THE PRODUCT DEVELOPMENT AT LABORATORY LEVEL THAN PILOT PLANT WHERE THE PRODUCT IS MANUFACTURED IN 10X THAN FINAL AT 100X THAT IS SCALE UP PLANT.
• Fragment Libraries
• Screening compounds
• Large collection of building blocks and intermediates
• PROTACs
• Custom and contract synthesis
• Scale up and route development
• Stable label synthesis
Applications of click chemistry in drug discoveryrita martin
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his article focus mainly on click chemistry mechanisms and its applications, click chemistry is an easy way to generate substances quickly and reliably by joining small units together, with this ease of use mechanism, click chemistry as found its applications in various technologies especially in drug discovery ,medicinal chemistry, enzyme activity, chemistry natural products, material science, polymers, nanotechnology and bioconjugation
Speed up pharmaceutical compounds synthesisAdaBrown2007
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Chemical synthesis is commonly employed in compound preparation, especially for pharmaceutical applications. The appearance of synthesis chemistry helps to save cost both for researchers and practical usages. Take pharmaceutical field alone for example, medicine prices are greatly decreased since synthesis chemistry is widely applied. A recent advance in the field will furtherly boost the efficiency of synthesis while make it cheaper.
Enabling HTS Hit follow up via Chemo informatics, File Enrichment, and Outsou...Graham Smith
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Enabling HTS Hit follow up via Chemo informatics, File Enrichment, and Outsourcing The history of parallel chemistry for lead discovery at Pfizer Sandwich from begining to outsourcing
The Application of Non-Combinatorial Chemistry to Lead DiscoveryGraham Smith
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The Application of Non-Combinatorial Chemistry to Lead Discovery. The evolution of purified non-combinatorial libraries as the way forward in parallel synthesis. Given at Lab automation 2002 Palm Springs
The Role of High Speed Synthesis in Protein Kinase ApproachesGraham Smith
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The Role of High Speed Synthesis in Protein Kinase Approaches, and example of how deverse and purified compound libraries quickly developed leads for IKK2 project
An Integrated Approach To Drug Discovery Using Parallel SynthesisGraham Smith
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An Integrated Approach To Drug Discovery Using Parallel Synthesis. The history of parallel chemistry for lead discovery at Pfizer Sandwich from begining to outsourcing
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
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Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
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91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
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In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
DevOps and Testing slides at DASA ConnectKari Kakkonen
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My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
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Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Enhancing Performance with Globus and the Science DMZGlobus
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ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
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My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
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Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
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Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
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Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
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Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
2. reviews research focus DDT Vol. 6, No. 15 August 2001
This article describes the non-combinatorial approach
developed and used by our Library Design and Production
Group, and demonstrates that a combination of rational
design, careful synthesis and compound purification be- H2N
OH
H2N
OH
H2N
OH
fore testing can generate high quality biological data that O O O
result in novel leads and new drug discovery programmes.
Non-combinatorial chemistry O
Non-combinatorial chemistry is a phrase coined to express H2N
OH
H2N OH
H2N OH
the difference in strategy between our technique and com- O O
binatorial chemistry as it is more commonly applied. Drug Discovery Today
Combinatorial chemistry involves the use of all combi-
Figure 1. Six amino acids. Your task is to choose the two most
nations of a set of reagents to produce an ordered array of
diverse amino acids that should be selected as monomers for
products. For example, a combinatorial amide library syn- file enrichment. This is representative of the problem faced in
thesis starting with 80 amines and 60 acids would make combinatorial file enrichment, in which a small number of
4800 amide products (80 × 60). In non-combinatorial monomers have to be selected in an attempt to represent the
properties of a much larger set.
chemistry, the same reagent sets can be used, but the prod-
ucts would be individually chosen for synthesis, such that
the 80 amines and 60 acids might be used to select any used to select the representative building blocks. However,
number of products from 80 up to the combinatorial limit this is an approach with significant drawbacks; a typical
of 4800, and still use each reagent. This approach is also situation that might be faced in selecting 20 amino acids
called ‘cherry-picking’ by some groups. The key differential from a set of 100 is presented in Fig. 1.
is to allow the design, synthesis, purification and screening As a subset of the whole exercise of choosing 20 from
of any group of individual compounds from a virtual 100, two amino acids might have to be chosen from the
library, not just arrays of compounds. The drive for this set of six presented in Fig. 1. If you have been involved
strategy is the desire to exploit virtual libraries that are as in such an exercise, you will recognize the similarity of
large as possible in a powerful and flexible manner, while this situation with examples from your own experience.
retaining total control over the properties of each product. Although software packages might be able to make a
The approach is important in both file enrichment and selection, the truth is that there is no correct way to
lead optimization. makethis choice for a file enrichment library. Whichever
pair you choose, they clearly cannot adequately represent
Application of non-combinatorial chemistry to file all six. Once you have made your selection of a pair of
enrichment amino acids, remember that in this library of 8000 com-
Non-combinatorial chemistry is important in file enrich- pounds, each of those amino acids will be present in 400
ment in that it allows the synthesis of diverse sets of com- products (in combination with the 20 selected amines and
pounds, using as many monomers as possible, not just a 20 selected carboxylic acids). The other four amino acids
small subset. The reason why this is important is best will be present in no products at all.
illustrated by an example. Consider a three component An alternative approach is to construct the 8000
library, represented as A–B–C. Let us assume that A are compounds in a non-combinatorial manner, using all the
amines, B are amino acids and C are acids, so the products available building blocks. In this example, if each of the
will be diamides. It can be easy to acquire 500 amines, 100 components A, B and C is used equally, each amine and
amino acids and 500 carboxylic acids from commercial carboxylic acid would be present in 16 (8000/500) prod-
sources, giving a virtual library size of 25 million ucts, and each amino acid in 80 (8,000/100) products.
compounds. Clearly, it is unlikely that 25 million single Arbitrary choices of monomers no longer need to be made
compounds will be synthesized using parallel synthesis. – all can be used in the file enrichment library – thus pro-
Therefore, a choice has to be made as to how to exemplify viding much greater diversity of products. The preparation
this virtual library (with perhaps 8000 examples) in a for synthesis of such a library does take longer than for a
compound collection for screening purposes. A typical combinatorial array (it takes longer to weigh and solubilize
approach might be to select 20 amines, 20 amino acids and 1100 components than 60). In addition, automation is
20 carboxylic acids to give a combinatorial array of 8000 now essential for synthesis because neat arrays that could
examples. Frequently, diversity-based methods might be be handled manually are no longer being used.
780
3. DDT Vol. 6, No. 15 August 2001 research focus reviews
A further significant benefit of the
20,000
non-combinatorial approach is that
you can choose not to synthesize spe-
Count of products
16,000
cific products, and thus precisely tailor
the physicochemical properties of the 12,000
non-combinatorial set. For example, it
is straightforward to calculate the prop- 8000
erties of the products and to ensure
4000
that all of those to be synthesized
0
should comply with certain distribu-
150
190
230
270
310
350
390
430
470
510
550
590
630
670
110
tions of molecular weight or clogP
values, Lipinski’s rule of five6 or other Molecular weight
desired properties. An example of the 20,000
effect of this flexibility can be seen in
Count of products
Fig. 2. 16,000
The standard combinatorial array
would give something approaching a 12,000
normal distribution of a property such
8000
as molecular weight. However, with
non-combinatorial synthesis, you can 4000
synthesize only those products with 0
150
190
230
270
310
350
390
430
470
510
550
590
630
670
110
molecular weights below a given value
or in a given value-range. Our in-house Molecular weight
library design software, S1D (selection Drug Discovery Today
in one dimension, i.e. by additive
or approximately additive fragmental Figure 2. An illustration contrasting property distribution in a combinatorial selection
with that in a non-combinatorial selection. Well-defined property cut-offs can be readily
properties, such as molecular weight or achieved via non-combinatorial approaches.
clogP) allows for the application of
these design principles and has been
used to select diverse libraries of specific design for file be searched by computational techniques, such as pharma-
enrichment for three years. S1D makes pseudo-random cophore searching or crystal structure ‘docking’, and the
selections of products from a virtual library in a way that hit-lists synthesized as they are or manipulated further.
attempts to use each monomer an equal number of times,
but with boundary conditions such that the calculated Non-combinatorial synthesis using LiCRA
properties of each product (molecular weight, clogP, and Our first significant problem was that at the time we
so on) fall within predetermined limits. S1D links to the started, nobody had considered that non-combinatorial
Library Creation, Registration and Automation system synthesis would ever be a user requirement of ‘combina-
(LiCRA). Both LiCRA and S1D were written by the torial chemists’, and still many do not. We were drawn to
chemoinformatics and Discovery Research informatics our solution by the knowledge that our HTS groups used
groups in Pfizer Global R&D, Sandwich, UK. ‘cherry-picking’ software on Tecan liquid handling robots
(Tecan UK, Reading, UK) to choose active compounds from
Application of non-combinatorial chemistry to lead HTS screening plates. However, no software was available
optimization at that time for our library synthesis task, because of our
Although non-combinatorial synthesis offers significant unique in-house requirements, and we decided, therefore,
benefits in file enrichment, the strategy is particularly pow- to design and build LiCRA ourselves.
erful once there are some design principles to apply, such When our group started work in 1997, we used each
as when an active compound or a crystal structure is in piece of automation in isolation to try to understand what
hand. Non-combinatorial synthesis gives the medicinal inputs and outputs were important for us to monitor and
chemist complete freedom to choose any selection of change. In general, most commercial automation runs on
single compounds from a given virtual library to expand its own software with minimal opportunities for broader
upon this structural information. Virtual libraries can also integration. A flat file can often be read to load sample data
781
4. reviews research focus DDT Vol. 6, No. 15 August 2001
and a further file is often written to the workstation to log All chemical incubations are performed off-line in simple
automation activity. Our first attempt at synthesis software shakers or ovens, and all products are sent through our
simply read flat files from a shared network drive and pro- in-house autopurification system (see later). Samples are
duced an input file for the next step of the process. This reformatted into 96-well Micronics plates (Micronics,
proved successful and was flexible in the event of machine Redmond, WA, USA) for registration that allows a final
errors. User intervention and file manipulation, however, quantitation by weighing to be performed using a Bohdan
was causing problems with tracking, and serious human Weighing Station (Mettler-Toledo Myriad, Royston, UK).
errors were increasing. The user is then presented with quality-control data on a
The latest version of LiCRA is based around an Oracle plate-by-plate basis to allow review of spectra and individual
database (Oracle UK, Reading, UK) of the individual com- sample data before registration.
pound batches that we have chosen to make. Their non- LiCRA has built-in links to several chemical structure
combinatorial selection means that, compared with array databases to allow easy analysis of monomer solubility, re-
synthesis, there is much less common data from one batch activity and other properties. Product structures are also
in a library to the next. Our main reasons for moving to a stored within the LiCRA database to allow more chemically
database-centred system were to increase storage and secu- intuitive quality control. Because all synthesis information
rity and to facilitate data analysis and trend recognition. is stored within the database, trends in solubility and reac-
Compliance with data storage and retrieval requirements tivity of individual monomers can be tracked to enhance
for patent purposes made us look into this more robust the quality of future libraries. When the chemist is satis-
approach. fied with the library products, a structure definition file,
The LiCRA user deals with a Visual Basic interface, which which contains all relevant information, is produced and
treats all the compounds in a library together (e.g. reaction sent to our compound control centre for registration to the
temperature, molar equivalents) but tracks most other data corporate database.
at the individual compound level (e.g. yield, purity and
protecting groups). A simple input interface that requires Automated purification of compounds from non-
the product structure in MDL (Molecular Design Ltd, combinatorial synthesis
Camberley, UK) Structure definition (SD) file format, The non-combinatorial chemistry approach to file enrich-
and an ASCII (American Standard Code for Information ment and lead optimization, as described earlier, generates
Interchange) file containing compound numbers with con- large numbers of single compounds, all of which need to
stituent monomers, is all that is required to load a library. be purified to minimize the presence of impurities and the
Typical libraries range from 200 to 2000 compounds. In generation of false-positives in biological screens. Analysis,
planning a synthetic scheme, volumes, equivalents and so purification and quantitation of large numbers of com-
on, can be entered for a whole library but can also be pounds in 96-well plate format has been viewed by many
altered on a monomer-by-monomer basis. An automatic as a highly labour intensive process. Systems are available
reservation can be made against the monomer inventory for high-throughput purification (e.g. the Biotage Parallex
system and lists of quantities printed if required. Monomers Flex™ system – Dyax, Charlottesville, VA, USA). However,
that appear in the library design but are not present at all, there are currently no commercial purification systems on
or are in insufficient quantity in the monomer store, are the market that can effectively process, quantify and track
flagged for intervention. The LiCRA inventory control large numbers of compounds in an automated way. The
system interfaces directly with accurate balances during key to any automated purification system is a fully inte-
weighing and calculates the exact amount of each monomer grated sample tracking process, coupled with proven
weighed. The weighed monomer samples are bar-coded purification technology and linked to a user-friendly soft-
and loaded into racks for synthesis. LiCRA produces a re- ware interface. A useful review of automated purification
port that warns when monomers are below a predetermined methodologies and emerging supercritical fluid chro-
re-order level, so that the inventory can be maintained. matography-based methods is available7.
The LiCRA synthesis system uses several standard and We have developed an autopurification system based on
robust pieces of commercial hardware. All solution dis- gradient HPLC separation, off-line MS analysis of fractions
pensing activities are performed by Tecan Genesis liquid and quantification by light scattering that has the capacity
handling robots, which have a proprietary interface for to purify up to 100,000 compounds per year at the 10–50 mg
non-combinatorial sample distributions. Specific racks and scale. The software interface (OmniTrak, developed by
boxes have been custom-made to enable inert atmosphere, Aitken Scientific, Thame, UK) is fully integrated with
corrosive reagent and solid-phase chemistry capabilities. LiCRA, and controls all the HPLC, MS and robotic hardware
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5. DDT Vol. 6, No. 15 August 2001 research focus reviews
involved in the purification process.
There are eight semi-preparative HPLC
systems [Gilson 306 gradient systems,
with Gilson 215 liquid handlers config-
ured as both autosamplers and fraction
collectors, operating under Unipoint
control software (Gilson, Middleton,
WI, USA)]. The HPLCs all use simple
generic gradients to effect separation
and purification (acetonitrile–0.1% tri-
fluoroacetic-acid gradients running
from 5–95% organic over 8 min at 4 ml
min–1 with a total run time of 15 min).
Each 96-well compound plate has a
barcode generated from LiCRA linked
to database records describing the 96
expected compounds and assigning an
empirical formula to each well. Each of
Figure 3. A view of part of the autopurification system: the linear track ORCA® robot
the 96 compounds is fractionated by
plate-handler (Beckman Coulter, Fullerton, CA, USA) is housed in a recirculating safety
gradient HPLC into bar-coded 48-well cabinet. The MS and evaporative light scattering unit are situated below the bench on
plates, collecting up to five fractions the right-hand side. Some of the eight semi-prep HPLCs can be seen in the
per compound using UV-triggered frac- background.
tion collection. The 48-well plates are
manually loaded onto a carousel and
an ORCA® robot then automatically (a) (b)
transfers the plate to a Gilson 231 auto-
sampler for analysis (Fig. 3). Each
fraction well is analyzed by flow
injection MS (Micromass® Platform
LC, Micromass® UK, Manchester, UK)
that operates in parallel with evap-
orative light scattering (Sedex Sedere
55, Thomson Instrument Company,
Chantilly, VA, USA). The MS identifies
the fraction or fractions with the (c) (d)
expected empirical formula for each
of the 96 compounds throughout
the series of 48-well fraction plates.
The evaporative light-scattering data
provides an estimate of the amount
of compound present in the fraction
by reference to a calibration file8. The
correctly identified fractions that
have sufficient sample mass are then
Figure 4. (a) A plate view from the LiCRA system, illustrating the connectivity between
automatically selected and compressed
the 96-well plate of products and all of the associated structural, analytical and synthetic
into a bar-coded plate of tared 5 ml information. The colour coding illustrates success (green) or failure (red) of the
Micronics tubes to be evaporated to chemistry at the well level. (b) A typical dual wavelength UV chromatogram of the crude
dryness (Genevac, Ipswich, UK). After product from a library synthesis. (c) Positive- and negative-ion electrospray MS of the
desired fraction (fraction 61, vial 13) from the purification of this crude product. (d) A
autopurification, all the MS and chro- typical 1[H] NMR showing the quality of compounds obtained using this autopurification
matographic data on any compound system.
can be accessed from within LiCRA.
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6. reviews research focus DDT Vol. 6, No. 15 August 2001
Using this technology, library chemists can purify their
R2 R1
compounds without involving themselves in the detailed Cl N
R5 1) R1R2NH R5
understanding of HPLC or MS, as all the identification, N N
analysis and quantification is carried out in an automated 2) R 3R4NH R3
R6 N Cl R6 N N
way. Compounds purified in this high-throughput and
R4
automated fashion are of comparable quality with those
R2 R1
produced by traditional synthesis and purification technol- Cl N
ogies; they are typically of 90–95% purity (Fig. 4). All the R5 1) R1R2NH R5
N N
compounds are tracked from their synthesis to registration N N
6 6
using a combination of OmniTrak and LiCRA, and all the R 2) R3R4NH R
Cl N
analytical data for a particular compound are linked to that R4 R3
tracking process. R2
R5 N Cl 1) R1R2NH R5 N N
R1
Application of S1D and LiCRA non-combinatorial
R3
chemistry to hit-to-lead optimization R6 N Cl 2) R3R4NH R6 N N
We have applied the S1D and LiCRA systems to several tar- R4
get types. The example that follows illustrates the power of R1, R2, R3, R4
= H, lower alkyl, cycloalkyl, substituted alkyl,
substituted cycloalkyl, heteroaryl, benzyl
the technology to optimize some weak hits coming from a
kinase screen to generate multiple, potent leads for chem- R5, R6 = H, lower alkyl, cycloalkyl, substituted alkyl,
istry follow-up. Five thousand compounds were selected substituted cycloalkyl, heteroaryl, benzyl, fused aryl,
fused heteroaryl, fused cycloalkyl
using S1D for non-combinatorial synthesis from a virtual Drug Discovery Today
library of 300,000 compounds that was designed specifi-
Figure 5. The design for some of the diamino-substituted
cally for a kinase screen. Figure 5 illustrates the type of aromatic heterocycles used in the kinase virtual library. This
chemistry used in this library subset. Figure 6a shows that library employed simple, solution-phase, chlorine displacement
the only activity observed on screening these compounds chemistry using large available monomer sets in 96-well
polytetrafluoroethylene plates.
came from three members of a subset of 700 compounds
made from just two templates: all other templates (4300
compounds) were inactive. The three active compounds avoid the selection of high molecular weight and lipophilic
were repeatedly tested and had IC50 values of 5–10 µM. The compounds that would occupy the top right-hand side of
hits were followed up by non-combinatorial synthesis of a the charts, because of the way in which the monomer lists
closed-loop subset of 693 compounds from the same vir- were ordered. The fifth and sixth loops delivered three dif-
tual library, focussing in on the regions of chemical space ferent series of selective and potent compounds with activ-
occupied by the three original hits and related regions ity against the kinase in the region of 10–50 nM. All of the
(Fig. 6b). This subset gave a respectable 2.3% hit rate at 2500 rule-of-five6 compliant compounds made in the six
10 µM. Furthermore, repeating the screening with solid closed-loops were synthesized as singletons, each one of
samples for some of the more active compounds gave the which was analyzed and autopurified as described above;
same Ki values, reinforcing our confidence in the identity all with less than one ‘person-year’ of effort. The leads we
and quality of the parallel synthesis-derived liquid samples discovered have provided the basis for a chemistry-staffed
used in the screens. lead-optimization project, which is now under way.
The early SAR information generated from this first
closed-loop prompted the synthesis of a second loop of Conclusions
345 compounds, which gave an impressive 66% hit rate We have demonstrated that non-combinatorial chemistry
against the enzyme at 10 µM (Fig. 6c). These compounds is an effective method for screening-file enrichment and
had improved solubility, and exhibited weaker activity and for lead optimization. We believe that whatever strategy is
independent SARs against key kinase-selectivity targets. used for library chemistry, the quality of design and the
Another 1400 compounds were made in four succeeding quality of the products are of paramount importance; we
closed-loops, in the course of which the virtual library was have achieved this with our S1D and LiCRA systems. We
expanded from 300,000 to 4,600,000 compounds by the intend to build upon this system in the future and add new
addition of further custom and commercial monomers. A design tools and new synthetic capabilities to expand the
summary of the outcome of all six closed-loops is shown in scope and quality of the virtual chemistry space accessible
Fig. 6d. It is clear from Fig. 6a–d that S1D has been used to to our chemists.
784
7. DDT Vol. 6, No. 15 August 2001 research focus reviews
(a) (b)
(c) (d)
Figure 6. (a) Non-combinatorial selection of 700 compounds from a virtual library of 300,000 in two templates: yellow and dark-blue
diamonds. The three active compounds are circled in red. Each axis of the chart consists of a list of the amine monomers used in each
position around the aromatic core. The x-axis corresponds to the amines used to displace the most reactive chlorine, the y-axis to the
amines used in the displacement of the second, less reactive chlorine. The amines were ordered by similarity (according to a judgement
made by medicinal chemists; see Fig. 7 for design outline). (b) A corresponding view of the 693 compounds made in the first closed loop
in response to the three hits found in Fig. 8a. The original 700 compounds screened are represented as green dashes; the 693 new
compounds in the first loop are shown as blue diamonds (inactive) and red circles (active); the three original hits upon which the SAR was
based are still shown circled in red. In this display, some of the compounds synthesized sit on top of one another in the chart, as multiple
templates sometimes shared the same monomer pairings; this third dimension of the data is missing from this compressed 2D view.
(c) Corresponding figure for the second closed-loop; all previous compounds are now shown as green dashes, and the second loop
compounds as blue diamonds (inactive) or red circles (active); again, this is a compressed 2D view of a 3D dataset. (d) A compressed 2D
representation of all six closed-loops (CLs). The compounds from the six loops are represented with the following symbols: CL1, yellow
triangles; CL2, magenta squares; CL3, blue diamonds; CL4, brown circles; CL5, open red diamonds; CL6, blue dashes; two groups of file
compounds are shown as crosses and as crossed crosses.
Acknowledgements References
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We are grateful for the expert assistance provided in hard-
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ware development, automation, information systems, 2 Hird, N.W. (1999) Automated synthesis: new tools for the organic
chemistry and screening by the following Pfizer colleagues: chemist. Drug Discov. Today 4, 265–274
3 Dolle, R.E. (2000) Comprehensive survey of combinatorial library
Mark Kemp, John Taylor, Pam Greengrass, Duncan Armour synthesis: 1999. J. Comb. Chem. 2, 383–433
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Hibbard and Grant Cameron of Anachem and Jeremy Batt 7 Ripka, W.C. et al. (2001) High-throughput purification of compound
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